import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


_SCREAMING_SNAKE_CASE 		=      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE 		=      {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_SCREAMING_SNAKE_CASE 		=      {
    """vocab_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-german-cased""": """https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt""",
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-german-cased""": (
            """https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"""
        ),
    },
}

_SCREAMING_SNAKE_CASE 		=      {
    """distilbert-base-uncased""": 5_1_2,
    """distilbert-base-uncased-distilled-squad""": 5_1_2,
    """distilbert-base-cased""": 5_1_2,
    """distilbert-base-cased-distilled-squad""": 5_1_2,
    """distilbert-base-german-cased""": 5_1_2,
    """distilbert-base-multilingual-cased""": 5_1_2,
}


_SCREAMING_SNAKE_CASE 		=      {
    """distilbert-base-uncased""": {"""do_lower_case""": True},
    """distilbert-base-uncased-distilled-squad""": {"""do_lower_case""": True},
    """distilbert-base-cased""": {"""do_lower_case""": False},
    """distilbert-base-cased-distilled-squad""": {"""do_lower_case""": False},
    """distilbert-base-german-cased""": {"""do_lower_case""": False},
    """distilbert-base-multilingual-cased""": {"""do_lower_case""": False},
}
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase		):
   __lowerCAmelCase           =				VOCAB_FILES_NAMES
   __lowerCAmelCase           =				PRETRAINED_VOCAB_FILES_MAP
   __lowerCAmelCase           =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowerCAmelCase           =				PRETRAINED_INIT_CONFIGURATION
   __lowerCAmelCase           =				["""input_ids""", """attention_mask"""]
   __lowerCAmelCase           =				DistilBertTokenizer







   def __init__(     self						:						Dict   ,   lowerCamelCase_						:						Optional[Any]=None   ,   lowerCamelCase_						:						Union[str, Any]=None   ,   lowerCamelCase_						:						Any=True   ,   lowerCamelCase_						:						int="[UNK]"   ,   lowerCamelCase_						:						List[Any]="[SEP]"   ,   lowerCamelCase_						:						str="[PAD]"   ,   lowerCamelCase_						:						List[Any]="[CLS]"   ,   lowerCamelCase_						:						str="[MASK]"   ,   lowerCamelCase_						:						Tuple=True   ,   lowerCamelCase_						:						Union[str, Any]=None   ,   **lowerCamelCase_						:						List[str]   ,   ):





    """simple docstring"""


    super().__init__(
        lowerCamelCase_   ,   tokenizer_file=lowerCamelCase_   ,   do_lower_case=lowerCamelCase_   ,   unk_token=lowerCamelCase_   ,   sep_token=lowerCamelCase_   ,   pad_token=lowerCamelCase_   ,   cls_token=lowerCamelCase_   ,   mask_token=lowerCamelCase_   ,   tokenize_chinese_chars=lowerCamelCase_   ,   strip_accents=lowerCamelCase_   ,   **lowerCamelCase_   ,   )

    UpperCamelCase			  =      json.loads(self.backend_tokenizer.normalizer.__getstate__()				)
    if (
        normalizer_state.get("""lowercase"""   ,   lowerCamelCase_				) != do_lower_case
        or normalizer_state.get("""strip_accents"""   ,   lowerCamelCase_				) != strip_accents
        or normalizer_state.get("""handle_chinese_chars"""   ,   lowerCamelCase_				) != tokenize_chinese_chars
    ):
     UpperCamelCase			  =      getattr(lowerCamelCase_   ,   normalizer_state.pop("""type"""				)				)
     UpperCamelCase			  =      do_lower_case
     UpperCamelCase			  =      strip_accents
     UpperCamelCase			  =      tokenize_chinese_chars
     UpperCamelCase			  =      normalizer_class(**lowerCamelCase_				)

    UpperCamelCase			  =      do_lower_case







   def 						lowerCamelCase_	(     self						:						List[Any]   ,   lowerCamelCase_						:						Any   ,   lowerCamelCase_						:						Optional[int]=None				):





    """simple docstring"""


    UpperCamelCase			  =      [self.cls_token_id] + token_ids_a + [self.sep_token_id]

    if token_ids_a:
     output += token_ids_a + [self.sep_token_id]

    return output







   def 						lowerCamelCase_	(     self						:						Union[str, Any]   ,   lowerCamelCase_						:						List[int]   ,   lowerCamelCase_						:						Optional[List[int]] = None				):





    """simple docstring"""


    UpperCamelCase			  =      [self.sep_token_id]
    UpperCamelCase			  =      [self.cls_token_id]
    if token_ids_a is None:
     return len(cls + token_ids_a + sep				) * [0]
    return len(cls + token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]







   def 						lowerCamelCase_	(     self						:						Optional[Any]   ,   lowerCamelCase_						:						str   ,   lowerCamelCase_						:						Optional[str] = None				):





    """simple docstring"""


    UpperCamelCase			  =      self._tokenizer.model.save(lowerCamelCase_   ,   name=lowerCamelCase_				)
    return tuple(lowerCamelCase_				)

from __future__ import annotations
class SCREAMING_SNAKE_CASE_		:







   def __init__(     self						:						Dict   ,   lowerCamelCase_						:						str   ,   lowerCamelCase_						:						str				):





    """simple docstring"""


    UpperCamelCase  ,     UpperCamelCase			  =      text, pattern
    UpperCamelCase  ,     UpperCamelCase			  =      len(lowerCamelCase_				), len(lowerCamelCase_				)







   def 						lowerCamelCase_	(     self						:						List[Any]   ,   lowerCamelCase_						:						str				):





    """simple docstring"""


    for i in range(self.patLen - 1   ,   -1   ,   -1				):
     if char == self.pattern[i]:
      return i
    return -1







   def 						lowerCamelCase_	(     self						:						Union[str, Any]   ,   lowerCamelCase_						:						int				):





    """simple docstring"""


    for i in range(self.patLen - 1   ,   -1   ,   -1				):
     if self.pattern[i] != self.text[current_pos + i]:
      return current_pos + i
    return -1







   def 						lowerCamelCase_	(     self						:						Union[str, Any]				):





    """simple docstring"""


    UpperCamelCase			  =      []
    for i in range(self.textLen - self.patLen + 1				):
     UpperCamelCase			  =      self.mismatch_in_text(lowerCamelCase_				)
     if mismatch_index == -1:
      positions.append(lowerCamelCase_				)
     else:
      UpperCamelCase			  =      self.match_in_pattern(self.text[mismatch_index]				)
      UpperCamelCase			  =      (
          mismatch_index - match_index
      )  # shifting index lgtm [py/multiple-definition]
    return positions





_SCREAMING_SNAKE_CASE 		=      """ABAABA"""
_SCREAMING_SNAKE_CASE 		=      """AB"""
_SCREAMING_SNAKE_CASE 		=      BoyerMooreSearch(text, pattern)
_SCREAMING_SNAKE_CASE 		=      bms.bad_character_heuristic()

if len(positions) == 0:
     print("""No match found""")
else:
     print("""Pattern found in following positions: """)
     print(positions)
